In many major cities around the world, trip durations during peak traffic hours can be 5 to 10 times what they are in uncontested traffic. This results in significant additional costs in fuel, personal time, business productivity, and pollution. Congestion relief measures often take one of three forms:                1) increase system capacity by building more roads,        2) improve flows by adjusting signal timing, entry/exit controls, etc., or        3) improve flows by reducing the number of vehicles in any given region, road, or lane.        
The focus of the present disclosure is method 3—to increase flows by reducing the number of vehicles on the road (vehicle density). To understand the advantages of reducing vehicle density it's useful to look at the general relationship between vehicle density and overall traffic flow. The curve in the graph shown in FIG. 1 is representative of how traffic density (vehicles per mile along a road) effects vehicle flow (vehicles per hour passing a point).
The intersecting straight lines show vehicle speed at the intersection with the curve (flow divided by density). The absolute numbers should not be taken too literally, but the shape generally holds true, and it shows both how inefficient highly congested traffic is at utilizing available road capacity and how drastically vehicle density must be reduced from worst case congestion levels of greater than 200 vehicles per mile per lane (26 feet per vehicle) to maximize flow.
The roughly triangular curve shows that starting from zero, as vehicles are added total flow increases because there are more vehicles travelling at a seed limited only by individual driving practices and traffic regulations. As density approaches the peak of the curve, vehicle speed starts to decline as drivers slow in response to the higher density, and total flow starts to level off. Past the peak, adding more vehicles becomes counterproductive, reducing both total flow and individual vehicle speeds. Notice that there is a wide range of densities around the peak where flow remains about the same despite significant reductions in speed. Perhaps an intuitive explanation for this is the tendency for drivers in heavy traffic to space themselves approximately a fixed time apart (e.g. 1.5 seconds) to allow for reaction time and stopping distance. That fixed time spacing results in a fixed flow rate over a broad range of speeds.
Given the shape of the curve, the ideal maximum density to operate at is probably a little before the peak (point A), where flows are near optimum and vehicle speeds are still close to that of free flowing traffic. Operating in that region of the curve might require reducing vehicles on the road to a small fraction (20-30%) of worst case congestion levels, but individual vehicle speeds can be 5-10 times faster.
Many methods and systems are currently in use to reduce vehicle density. Some are very direct, such as mandating days of the week when certain vehicle license numbers cannot be on the road, while others are more indirect, such as improvements in public transportation and encouraging carpools. A very common method is to use tolls and fees to increase the cost of using the road. If the costs are high enough, a segment of the population will choose a route or transportation means that avoids that cost.
A disadvantage of existing cost-driven methods, however, is that they place an uneven burden on the driving population based upon financial status. Those that can afford to pay the toll are able to take advantage of the less congested restricted routes and lanes, while those who cannot must deal with even higher traffic densities on whatever roads or lanes are left. In this sense, they are not income neutral or fair. Also, because of this affordability constraint, their demand reduction effects help, but often fall far short of what would be necessary to maximize traffic flow efficiencies in highly oversaturated road systems.
Rather than organizing and managing the demand to actively and directly control traffic density, nearly all other congestion reduction methods in use in laces like Singapore, London, and Stockholm use demand reduction (i.e., use some other transportation method, go some other time, or don't go at all) as their primary target, and do so indirectly through cost disincentives.